با سلام خدمت کاربران در صورتی که با خطای سیستم پرداخت بانکی مواجه شدید از طریق کارت به کارت (6037997535328901 بانک ملی ناصر خنجری ) مقاله خود را دریافت کنید (تا مشکل رفع گردد).
ردیف | عنوان | نوع |
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31 |
X-PHM: Prognostics and health management knowledge-based framework for SME
X-PHM: پیش آگهی و چارچوب دانش مبتنی بر مدیریت سلامت برای SME-2021 Prognostics and Health Management (PHM) is an emerging concept based on industrial data management. The implementation of PHM in
small and medium-sized enterprises (SMEs) is currently limited due to data accessibility difficulties. In order to overcome this pitfall, one could
formalize the operators’ knowledge and integrate it in the SME’s information system. Thus, the implementation of the PHM will be based
on this information system associating data with knowledge. To this end, we propose a collaborative PHM approach (X-PHM) to ensure the
extraction of operators’ knowledge and its integration into the PHM process. The decision resulting from this approach is restituted with a concern
of explainability. This paper details the proposed approach while focusing on the data management process and its integration in explainable
decisions. This new framework is applied in a French SME to understand its production process and facilitate its digital transformation.
Keywords: PHM | Knowledge formalization and integration | Explainable artificial intelligence | SME | Data analysis. |
مقاله انگلیسی |
32 |
Mental accounting and consumption of self-produced food
حسابداری ذهنی و مصرف غذای خود تولیدی-2021 This is an exploratory study on mental accounting and food budgeting of agricultural households, in which we assumed
that agricultural households may have a mental account for consumption of their self-produced food. Accordingly, they
may reserve a certain quantity of self-produced food as a set budget for own consumption, implying that they may
keep on consuming their own produce until they have consumed the quantity set for the mental budget. By making the
mental accounting assumption, we hypothesized that the consumption of self-produced food is independent of market
price. Also, we hypothesized that the consumption of self-produced food is increasing in the quantity of production if
production is lower than the set budget, and independent of the quantity of production if production exceeds the set
budget. By applying a double-log demand model and using survey data from six poor rural counties in China, we tested
these hypotheses for five food items, which are rice, flour, potatoes, pork, and eggs. We found that the hypothesis of no
significant effect of price holds for flour, potatoes, and pork if production is lower than the set budget, and for rice, pork,
and eggs if production is higher than the set budget. Production has a significant positive effect on consumption of selfproduced food but with a much greater influence when production is lower than the set budget for all five food items.
These findings partly support our assumption of mental accounting of self-produced food. Limitations, policy implications,
and possible future studies are discussed.
Keywords: mental accounting | food consumption | self-produced food | agricultural household |
مقاله انگلیسی |
33 |
A study related to product service systems (PSS), SERVQUAL and knowledge management system (KMS) – A review
مطالعه مربوط به سیستم های خدمات محصول (PSS)، SERVQUAL و سیستم مدیریت دانش (KMS) - یک مرور-2021 PSS is a growing field of research in industry practice in today’s global economy. It is a new trend that has
an impact on both the production and consumption of resources. PSS aims at a more profitable and conservational usage of products. While in the past providing services was one of the strategies attained to
differentiate in competition, however today providing a product together with many services has become
a standard practice in the product industry. To remain competitive, manufacturers are forced not only to
produce a competitive product however rather a superior PSS.PSS are outlined as life cycle bound combinations of a product and completely different services, having sophisticated networks, that comprise a
manufacturer as a provider and also as a repair partner. To enable the applicability of a PSS in an industry,
it is essential to evaluate the system using metrics – the SERVQUAL MODEL, which defines ‘‘The quality as
the difference between the customers’ expectations & perceptions concerning the services delivered to
them” [1]. It is catered to measure quality by capturing the expectancy – confirmation paradigm which
suggests the consumer’s perceived quality of how well a given service delivery meets their expectations
of that delivery. So this SERVQUAL metric is used to determine the level of quality in the industry and the
five dimensions are such as tangibility, reliability, responsiveness, assurance & empathy are measured
using a five-point Likert scale. Since, organizations are more and more moving towards knowledgebased strategies, developing and managing knowledge is essential for improving the organizational performance as well as for enhancing decision-making process. This paper presents a review on the use of a
knowledge management practice in PSS for industries to store, share and utilize knowledge for enhancing
creativity & innovation in their service systems. An efficient review of the literature has been conducted
in the academic and scientific databases taking into account the date of publication of the articles titled
PSS, SERVQUAL and KMS from 2009 to 2020. To achieve the review process, all selected articles have been
categorized by publication year, the objectives of the research, the methodology used, the results, conclusion and future scope of their research are presented on a broader scale [16]. Therefore, this paper presents an overview of the literature on PSS and the evaluation methods using SERVQUAL MODEL and the
role of knowledge management in PSS and the appropriate ideas for conducting research in the future.
Copyright 2021 Elsevier Ltd. All rights reserved.
keywords: سیستم خدمات محصول | مدل SERVQUAL | سیستم مدیریت دانش | تصمیم گیری | Product service system | SERVQUAL MODEL | Knowledge management system | Decision-making |
مقاله انگلیسی |
34 |
Lessons learned from development of natural capital accounts in the United States and European Union
درس های آموخته شده از توسعه حساب های سرمایه طبیعی در ایالات متحده و اتحادیه اروپا-2021 The United States and European Union (EU) face common challenges in managing natural capital and balancing
conservation and resource use with consumption of other forms of capital. This paper synthesizes findings from
11 individual application papers from a special issue of Ecosystem Services on natural capital accounting (NCA)
and their application to the public and private sectors in the EU and U.S. NCA is inherently a data-integration
centered exercise, aiming to draw new insights by realigning environmental and economic data into a consis-
tent framework. Drawing primarily on papers from the special issue and other key NCA literature, we identify
lessons learned and gaps remaining for NCA’s development and application to decision making. In doing so, we
identify eight key similarities and three major differences in NCA development, status, and application between
the U.S. and EU. NCA can be highly policy relevant: special issue papers address critical issues including agri-
culture, water, conservation/land-use planning, climate, and corporate decision making. In both the U.S. and EU,
further application is needed to drive demand for the accounts’ production. Based on these experiences, the U.S.
and EU can be important leaders in cross-sector, international collaboration toward next-generation environ-
mental economic accounts that advance global NCA practice. keywords: حسابداری طبیعی سرمایه | حسابداری بخش خصوصی | سیستم حسابداری محیطی-اقتصادی- | ING (رادیو) | چارچوب مرکزی Seea | حسابداری اکوسیستم Seea | Natural capital accounting | Private-sector accounting | System of Environmental-Economic Account- | ing (SEEA) | SEEA Central Framework | SEEA Ecosystem Accounting |
مقاله انگلیسی |
35 |
On-farm experiences shape farmer knowledge, perceptions of pollinators, and management practices
تجارب در مزرعه دانش کشاورز، ادراکات گرده افشان ها و شیوه های مدیریتی را شکل می دهد-2021 Mitigating pollinator declines in agriculturally dominated landscapes to safeguard pollination
services requires the involvement of farmers and their willingness to adopt pollinator-friendly
management. However, farmer knowledge, perceptions, and actions to support on-farm pollinators and their alignment with science-based knowledge and recommendations are rarely
evaluated. To close this knowledge gap, we interviewed 560 farmers from 11 countries around
the world, cultivating at least one of four widely grown pollinator-dependent crops (apple, avocado, kiwifruit, oilseed rape). We particularly focused on non-bee crop pollinators which,
despite being important pollinators of many crops, received less research attention than bees. We
found that farmers perceived bees to be more important pollinators than other flower-visiting
insects. However, around 75% of the farmers acknowledged that non-bees contributed to the
pollination of their crops, seeing them as additional pollinators rather than substitutes for bees.
Despite farmers rating their own observations as being most important in how they perceived the contribution of different crop pollinator taxa, their perception aligned closely with results from
available scientific studies across crops and countries. Farmer perceptions were also linked with
their pollinator management practices, e.g. farmers who used managed bees for crop pollination
services (more than half the farmers) rated these managed bees as particularly important.
Interestingly, their willingness to establish wildflower strips or manage hedgerows to enhance
pollinator visitation was linked to their ecological knowledge of non-bees or to government
subsidies. Farmers adapted practices to enhance pollination services depending on the crop,
which indicates an understanding of differences in the pollination ecology of crops. Almost half of
the farmers had changed on-farm pollination management in the past 10 years and farm practices
differed greatly between countries. This suggests integrated crop pollination measures are being
adapted by farmers to reach best pollinator management practices. Our findings highlight the
importance of studying local knowledge as a key to co-design locally-adapted measures to
facilitate pollinator-integrated food production as ecological intensification tools.
keywords: حفاظت | گرده افشانی | تشدید زیست محیطی | دانش کشاورز | دانش محلی | نظر سنجی | Conservation | Crop pollination | Ecological intensification | Farmer knowledge | Local knowledge | Survey |
مقاله انگلیسی |
36 |
Time-sensitive supply chain disruption recovery and resource sharing incentive strategy
استراتژی تشویقی برای بهبود اختلال در زنجیره تأمین حساس به زمان-2021 Market demand is becoming increasingly time-sensitive in competitive environments. Hence, supply disruptions will have a more serious impact on the profits of supply chains. This study applies a Stackelberg competition between a single supplier and a single manufacturer in a time-sensitive supply chain in a cloud manufacturing environment. We aim to address the supplier’s production capacity recovery issues and the manufacturer’s incentive decision issues after supply disruption. We find that the supplier is in a weak position when the information is symmetrical. The manufacturer can encourage the supplier to shorten the recovery time by raising the unit wholesale price. When the supplier’s unit production cost remains unchanged but the unit wholesale price increases, the profit of the supplier first increases and then decreases. In addition, under the centralized decision-making setting, the optimal recovery time of the supplier is shorter and the optimal unit market price of the product is lower than that under decentralized decision-making. We further find that resource sharing can shorten the optimal recovery time, but it does not necessarily play an incentivizing role.© 2021 China Science Publishing & Media Ltd. Publishing Services by Elsevier B.V. on behalf of KeAi Communications Co. Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Keywords: Supply chain | Time-sensitive | Supply disruption | Resource sharing |
مقاله انگلیسی |
37 |
Biomass supply chain coordination for remote communities: A game-theoretic modeling and analysis approach
هماهنگی زنجیره تأمین زیست توده برای جوامع از راه دور: رویکرد مدل سازی و تحلیل نظری بازی-2021 Biomass, as one of the most available renewable energies, could reduce dependency on fossil fuels and the consequent environmental impacts. There is a need for biomass supply chain management, which is managing bioenergy production from harvesting feedstock to energy conversion facilities. In case of remote communities, bioenergy adoption requires dealing with dispersed geographies of suppliers and places of consumption with small scales of energy demand. As such, coordination plays a key role in increasing the efficiency of the biomass supply chain network through bundling of demand and thus improving the economy of scale. This paper employs a game-theoretic approach to formulate a coordinated biomass supply chain with three echelons including suppliers, hubs, and energy convertors. To investigate the strategic interactions of participants, three decision making structure scenarios have been considered under Stackelberg game providing insights into the impact of power distribution, the role of side payments in enforcing the flow of decisions, and the resulting efficiency and performance improvements. In doing so, a case study bioenergy supply chain for three northern Canadian communities is explored to demonstrate the application of the proposed formulation, solution methods, and the practicality and significance of the adopted approach and outcomes for remote communities. Keywords: Bioenergy | Supply chains | Coordination | Remote communities | Game theory | Mathematical Program with Equilibrium | Constraints (MPEC) |
مقاله انگلیسی |
38 |
Bi-objective optimal design of hydrogen and methane supply chains based on Power-to-Gas systems
طراحی بهینه دو هدفه زنجیره های تأمین هیدروژن و متان بر اساس سیستم های نیرو به گاز-2021 This paper presents a methodological design framework for Hydrogen and Methane Supply Chains (HMSC) based on Power-to-Gas (PtG) systems. The novelty of the work is twofold, first considering a specific demand for hydrogen for electromobility in addition to the hydrogen demand required as a feedstock to produce synthetic methane from the methanation process. and performing a bi-objective optimization of the HMSC to provide effective support for the study of deployment scenarios. The approach is based on a Mixed Integer Linear Programming (MILP) approach with augmented epsilon-constraint implemented in the GAMS environment according to a multi-period approach (2035-2050) with several available energy sources (wind, PV, hydro, national network) for hydrogen production. Carbon dioxide sources stem mainly from mechanization and gasification processes. The objectives to be minimized simultaneously are the Total Annual Cost and the greenhouse gas emissions related to the whole HMSC over the entire period studied. KEYWORDS: Power-to-Gas | Methanation | Hydrogen | MILP | Augmented epsilon constraint | GAMS | optimization approach |
مقاله انگلیسی |
39 |
Data Driven Robust Optimization for Handling Uncertainty in Supply Chain Planning Models
بهینه سازی قوی مبتنی بر داده ها برای مدیریت عدم قطعیت در مدل های برنامه ریزی زنجیره تامین-2021 While addressing supply chain planning under uncertainty, Robust Optimization (RO) is regarded as an efficient and tractable method. As RO involves calculation of several statistical moments or maximum / minimum values involving the objective functions under realizations of these uncertain parameters, the accuracy of this method significantly depends on the efficient techniques to sample the uncertainty parameter space with limited amount of data. Conventional sampling techniques, e.g. box/budget/ellipsoidal, work by sampling the uncertain parameter space inefficiently, often leading to inaccuracies in such estimations. This paper proposes a methodology to amalgamate machine learning and data analytics with RO, thereby making it data-driven. A novel neuro fuzzy clustering mechanism is implemented to cluster the uncertain space such that the exact regions of uncertainty are optimally identified. Subsequently, local density based boundary point detection and Delaunay triangulation based boundary construction enable intelligent Sobol based sampling to sample the uncertain parameter space more accurately. The proposed technique is utilized to explore the merits of RO towards addressing the uncertainty issues of product demand, machine uptime and production cost associated with a multiproduct, and multisite supply chain planning model. The uncertainty in supply chain model is thoroughly analysed by carefully constructing examples and its case studies leading to large scale mixed integer linear and nonlinear programming problems which were efficiently solved in GAMS framework. Demonstration of efficacy of the proposed method over the box, budget and ellipsoidal sampling method through comprehensive analysis adds to other highlights of the current work. Keywords: Uncertainty Modelling | Supply chain Management | Data driven Robust Optimization | Neuro Fuzzy Clustering | Multi-Layered Perceptron |
مقاله انگلیسی |
40 |
Information and Measurement System for Electric Power Losses Accounting in Railway Transport
اطلاعات و سیستم اندازه گیری برای حسابداری تلفات برق در حمل و نقل ریلی-2021 The purpose of the presented research is to minimize the loss of electricity during the operation of railway power systems. Losses
are defined as an unbalance between the released and consumed electricity, which is recorded by means of commercial electricity
ccounting. Given that electricity losses are divided into technical and non-technical (commercial) components, there are
currently no technical tools that can analyze the components of electricity losses in detail, and therefore prevent their occurrence.
To achieve this goal, the factors inherent in commercial electricity accounting systems in various areas of production activity that
affect the growth of electricity losses are identified. An algorithm is proposed that allows determining the presence of abnormal
power losses in real time for making organizational and technical decisions to reduce them. A block diagram of the information
and measurement system for accounting of power losses has been developed, which allows using the existing equipment without
replacement or modernization, which allows obtaining new technical capabilities. The method of intellectualization of the
process of classification of factors that cause the growth of abnormal power losses, based on artificial neural networks, is
posed. The intelligent module allows replacing the person who makes organizational and technical decisions, minimizing the
consequences of abnormal situations that lead to the growth of abnormal losses, applying the proposed solutions in departments
that do not have qualified specialists. The results of training an artificial neural network are considered, and the main parameters
of the efficiency of the information and measurement system for loss accounting on a real railway transport object are
determined.
Keywords: Power Loss | Artificial Neural Networks. |
مقاله انگلیسی |